250 lines
7.5 KiB
Plaintext
250 lines
7.5 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 22,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1.000\t1\t021365\n",
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"1.000\t2\t021366\n",
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"1.000\t3\t021367\n",
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"1.000\t4\t021368\n",
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"0.944\t5\t021369\n",
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"0.947\t6\t021370\n",
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"0.917\t7\t021372\n",
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"1.000\t8\t021371\n",
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"1.000\t9\t021373\n",
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"1.000\t10\t021374\n",
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"1.000\t11\t021375\n",
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"1.000\t12\t021376\n",
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"0.966\t13\t021377\n",
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"1.000\t14\t022022\n",
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"0.902\t15\t021379\n",
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"0.865\t16\t021382\n",
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"1.000\t17\t022023\n",
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"0.987\t18\t021383\n",
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"1.000\t19\t021384\n",
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"1.000\t20\t021385\n",
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"1.000\t21\t021386\n",
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"1.000\t22\t021387\n",
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"1.000\t23\t021389\n",
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"1.000\t24\t022024\n",
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"1.000\t25\t021390\n",
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"1.000\t26\t022026\n",
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"0.891\t27\t021392\n",
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"0.965\t28\t021393\n",
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"0.986\t29\t021394\n",
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"0.940\t30\t021395\n",
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"1.000\t31\t021396\n",
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"1.000\t32\t022027\n",
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"1.000\t33\t021397\n",
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"1.000\t34\t022028\n",
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"0.805\t35\t021401\n",
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"1.000\t36\t021403\n",
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"1.000\t37\t022029\n",
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"1.000\t38\t022030\n",
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"1.000\t39\t022031\n",
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"1.000\t40\t022032\n",
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"1.000\t41\t022033\n",
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"1.000\t42\t022034\n",
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"0.887\t43\t021410\n",
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"1.000\t44\t022035\n",
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"1.000\t45\t022036\n",
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"1.000\t46\t022037\n",
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"1.000\t47\t021413\n",
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"0.959\t48\t022038\n",
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"1.000\t49\t022039\n",
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"1.000\t50\t021415\n",
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"1.000\t51\t022040\n",
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"1.000\t52\t022041\n",
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"0.793\t53\t021418\n",
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"0.807\t54\t021420\n",
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"0.693\t55\t021421\n",
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"1.000\t56\t021422\n",
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"1.000\t57\t021423\n",
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"1.000\t58\t022042\n",
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"1.000\t59\t022043\n",
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"0.805\t60\t021427\n",
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"0.957\t61\t021425\n",
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"0.770\t62\t021428\n",
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"0.970\t63\t022044\n",
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"1.000\t64\t022045\n",
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"0.738\t65\t021430\n",
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"1.000\t66\t022046\n",
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"1.000\t67\t022047\n",
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"0.792\t68\t021432\n",
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"0.793\t69\t021434\n",
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"0.721\t70\t021433\n",
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"0.811\t71\t021435\n",
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"0.728\t72\t021436\n",
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"1.000\t73\t021437\n",
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"0.989\t74\t021438\n",
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"0.848\t75\t021440\n"
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]
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}
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],
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"source": [
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"import os,re,difflib,Levenshtein,time,json\n",
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"\n",
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"# 重要!!! 范围\n",
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"old_problems_range = \"21365:21440,22022:22047\"\n",
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"threshold = 0.85\n",
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"\n",
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"# 待比对的文件\n",
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"filename = r\"D:\\temp\\derivatives.tex\"\n",
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"\n",
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"#生成数码列表, 逗号分隔每个区块, 区块内部用:表示整数闭区间\n",
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"def generate_number_set(string):\n",
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" string = re.sub(r\"[\\n\\s]\",\"\",string)\n",
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" string_list = string.split(\",\")\n",
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" numbers_list = []\n",
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" for s in string_list:\n",
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" if not \":\" in s:\n",
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" numbers_list.append(s.zfill(6))\n",
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" else:\n",
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" start,end = s.split(\":\")\n",
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" for ind in range(int(start),int(end)+1):\n",
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" numbers_list.append(str(ind).zfill(6))\n",
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" return numbers_list\n",
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"\n",
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"#字符串预处理\n",
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"def pre_treating(string):\n",
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" string = re.sub(r\"\\\\begin\\{center\\}[\\s\\S]*?\\\\end\\{center\\}\",\"\",string)\n",
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" string = re.sub(r\"(bracket\\{\\d+\\})|(blank\\{\\d+\\})|(fourch)|(twoch)|(onech)|(mathrm)|(text)\",\"\",string)\n",
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" string = re.sub(r\"[\\s\\\\\\{\\}\\$\\(\\)\\[\\]]\",\"\",string)\n",
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" string = re.sub(r\"[\\n\\t]\",\"\",string)\n",
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" string = re.sub(r\"(displaystyle)|(overrightarrow)\",\"\",string)\n",
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" string = re.sub(r\"[,\\.:;?]\",\"\",string)\n",
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" return string\n",
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"\n",
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"#difflab字符串比较\n",
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"def difflab_get_equal_rate(str1, str2):\n",
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" return difflib.SequenceMatcher(None, str1, str2).ratio()\n",
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"\n",
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"#Levenshtein jaro字符串比较\n",
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"def jaro_get_equal_rate(str1,str2):\n",
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" return Levenshtein.jaro(str1,str2)\n",
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"\n",
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"#Levenshtein 字符串比较\n",
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"def Lev_get_equal_rate(str1,str2):\n",
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" return Levenshtein.ratio(str1,str2)\n",
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"\n",
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"def GenerateProblemListFromString(data):\n",
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" try:\n",
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" data = re.findall(r\"\\\\begin\\{document\\}([\\s\\S]*?)\\\\end\\{document\\}\",problems_string)[0]\n",
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" except:\n",
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" pass\n",
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" data = re.sub(r\"\\n{2,}\",\"\\n\",data)\n",
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" data = re.sub(r\"\\\\item\",r\"\\\\enditem\\\\item\",data)\n",
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" data = re.sub(r\"\\\\end\\{enumerate\\}\",r\"\\\\enditem\",data)\n",
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" ProblemList_raw = [p.strip() for p in re.findall(r\"\\\\item([\\s\\S]*?)\\\\enditem\",data)]\n",
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" ProblemsList = []\n",
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" for p in ProblemList_raw:\n",
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" startpos = data.index(p)\n",
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" tempdata = data[:startpos]\n",
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" suflist = re.findall(r\"\\n\\%[\\dA-Za-z]+\",tempdata)\n",
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" if len(suflist) > 0:\n",
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" suffix = suflist[-1].replace(\"%\",\"\").strip()\n",
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" else:\n",
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" suffix = \"\"\n",
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" ProblemsList.append((p,suffix))\n",
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" return ProblemsList\n",
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"\n",
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"\n",
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"#指定对比方法\n",
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"sim_test = jaro_get_equal_rate\n",
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"\n",
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"#读入题库\n",
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"with open(r\"../题库0.3/Problems.json\",\"r\",encoding = \"utf8\") as f:\n",
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" database = f.read()\n",
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"pro_dict = json.loads(database)\n",
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"\n",
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"with open(filename,\"r\",encoding=\"u8\") as f:\n",
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" newdatabase = f.read()\n",
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"new_pro_list = GenerateProblemListFromString(newdatabase)\n",
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"\n",
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"pro_dict_treated = {}\n",
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"idrange = generate_number_set(old_problems_range)\n",
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"for p in idrange:\n",
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" pro_dict_treated[p] = pre_treating(pro_dict[p][\"content\"])\n",
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"\n",
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"new_dict_treated = {}\n",
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"for i in range(len(new_pro_list)):\n",
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" new_dict_treated[i+1] = pre_treating(new_pro_list[i][0])\n",
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"\n",
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"for i in new_dict_treated:\n",
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" new_p = new_dict_treated[i]\n",
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" maxsim = 0\n",
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" for p in pro_dict_treated:\n",
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" old_p = pro_dict_treated[p]\n",
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" sim = sim_test(new_p,old_p)\n",
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" if sim > maxsim:\n",
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" maxsim = sim\n",
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" argmax = p\n",
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" print(\"%.3f\\t%d\\t%s\" %(maxsim,i,argmax))\n",
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" # print(\"\\n新题: %s\" %new_pro_list[i-1][0])\n",
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" # print(\"\\n原题: %s\\n\\n\\n\" %pro_dict[][\"content\"])\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"75"
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]
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},
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"len(new_dict_treated)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "mathdept",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.15"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "42dd566da87765ddbe9b5c5b483063747fec4aacc5469ad554706e4b742e67b2"
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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